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Skip to Search Results- 49Artificial Intelligence
- 28Machine Learning
- 25Natural Language Processing
- 10Reinforcement Learning
- 8Bioinformatics
- 7Deep Learning
- 1Akbari, Mojtaba
- 1Alexander, Graham
- 1Asadi Atui, Kavosh
- 1Ashley, Dylan R
- 1Ashrafi Asli, Seyed Arad
- 1Atrazhev, Peter
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Spring 2023
With machine learning models becoming more complicated and more widely applied to solve real-world challenges, there comes the need to explain their reasoning. In parallel with the advancements of deep learning methods, Explainable AI (XAI) algorithms have been proposed to address the issue of...
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Fall 2023
In this thesis, we study the problem of performance prediction for open-domain multi-hop Question Answering (QA), where the task is to estimate the difficulty of evaluating a multi-hop question over a corpus. Despite the extensive research on predicting the performance of ad-hoc and QA retrieval...
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Motion Planning of Robotic Systems in Diagnostic and Therapy Applications Using Control and AI
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This thesis presents significant research on robotic motion planning within diagnostic and therapy applications, with a primary focus on the integration of control and AI techniques. The research encompasses three main contributions: a robotic ultrasound imaging method, a robot-assisted...
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Development of AI-based ergonomics risk assessment tools for harmonization of industrial work systems
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Manufacturing industry workers face significant ergonomic risks due to poorly designed work systems. Consequently, it is crucial to periodically assess work systems to identify areas for improvement. However, the assessment process is often disregarded due to the absence of userfriendly...
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Fall 2023
This thesis introduces a new approach for grounding concepts to vision using visual descriptions, which are text-based descriptions of visual attributes. We hypothesize that these descriptions can enhance the grounding of concepts to vision, thereby improving performance in vision-language tasks....
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{Multi-Agent Deep Reinforcement Learning for Autonomous Energy Coordination in Demand Response Methods for Residential Distribution Networks
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In the field of collaborative learning and decision-making, this thesis aims to explore the effects of individual and joint rewards on the performance and coordination of agents in complex environments. The research objectives encompass two main aspects: firstly, to determine the objective...
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An Exploration of Dialog Act Classification in Open-domain Conversational Agents and the Applicability of Text Data Augmentation
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Recognizing dialog acts of users is an essential component in building successful conversational agents. In this work, we propose a dialog act (DA) classifier for two of our open domain conversational agents. For this, we curated a high-quality, multi-domain dataset with ∼24k user utterances...
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Spring 2023
The gaming industry has experienced a sharp growth in recent years, surpassing other popular entertainment segments, such as the film industry. With the ever-increasing scale of the gaming industry and the fact that players are extremely difficult to satisfy, it has become extremely challenging...
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Spring 2023
Dialogue systems powered by large pre-trained language models exhibit an innate ability to deliver fluent and natural-sounding responses. Despite their impressive performance, these models fail to conduct interesting and consistent exchanges of turns and can often generate factually incorrect...
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Fall 2023
Many works of art are created through the process of an artist sketching and then incrementally increasing the fidelity of the artwork. This requires significant amounts of work and effort throughout, but not all steps require the same amount of artistic input. Certain parts only require...